Online shopping is a form of electronic commerce where goods and/or services can be bought, purchased, and/or traded using the Internet. For example, the goods and/or services may be located online by entering a search query into a web search engine, and allowing the search engine to search the Internet for the goods and/or services identified in the search query.
Web search engines typically rely on text matching for locating relevant goods and/or services on the Internet. However, in some instances, multiple users may formulate different search queries when looking for the same good and/or service. For example, a first user may formulate the search query “mattresses” when searching for a mattress, while a second user may formulate the search query “beds” when searching for a mattress. Since the search engine may not recognize the term “beds” as being synonymous with a mattress, the search engine may then recall and/or locate goods and/or services which are irrelevant to a mattress, such as bed frames, bedroom furniture, hotel rooms, etc.
Current methods of generating synonyms for a search query have utilized various out-of-the-box ontology technologies, which are typically formulated to generate synonyms of known products and/or services. However, such ontology technologies may not be able to recognize specific brand names, specific product names, and/or retail-specific jargon. Therefore, the ontology technology alone may not be able to generate most, if not all suitable synonyms for a search query.
Current methods of generating synonyms for a search query may also or alternatively analyze session logs for reformulating search queries. While suitable for head queries, analyzing query logs for query reformulation alone may not be as effective for generating usable synonyms for tail queries which may be due, at least in part, to lower online traffic and less available information for query reformulation.
The present disclosure is aimed at solving the problems identified above.